“You only get out of it what you put into it” is good workout advice. But it also happens to be good cloud advice.
Chances are, you’re either in the cloud or thinking about the cloud. Gartner predicts spending on public cloud services will reach nearly $600 billion in 2023.
But all this cloud spending is only worth it if you’re taking advantage of the cloud’s offerings, like powerful computing resources, scalability, and collaboration. And many organizations don’t get it right: Through 2024, 80% of companies will be unaware of their mistakes in their cloud adoption and will overspend by 20 to 50%, according to Gartner. That’s potentially $240 billion down the drain in 2023. Common mistakes? Failure to leverage the cloud for workloads that would benefit most and not involving the entire business in a cloud strategy.
It’s like getting a gym membership because you believe having access to a gym is a good investment for your fitness, but then you don’t actually work out because you don’t know how to use the elliptical. Suddenly you get hit with the bill at the end of the month, and you realize you’ve contributed to the $397 million spent on unused gym memberships! Much like a gym and life in general, you only get out of the cloud what you put into it.
Luckily, Alteryx makes it easy to take advantage of cloud for your data analytics. With partnerships and integrations across the cloud ecosystem – including AWS, Azure, and Google Cloud Platform (GCP) – Alteryx is designed to maximize the benefits of cloud.
Here are five ways Alteryx and its cloud partners can help you get the most out of cloud:
Make it easier to get the data in the first place.
You wouldn’t want to drive several hours to get to the gym before you can start a workout. And you also don’t want your team to spend hours hunting down data before they can start getting insights from it. According to a new IDC report, workers waste 51% of their time when searching for data. And data workers cited a “lack of the knowledge of data sources” as a top challenge. It can be like pulling teeth to find, request access, and collect the data before you even start using it.
Using Alteryx with cloud partners makes it easier to get data into the hands of the workers who need it – while also controlling access and governance. Snowflake, for example, provides a centralized cloud for data that’s secure, accessible and ready at all times for processing and analyzing with Alteryx. The faster workers can get to the data, the more they can do with it.
Pull off big projects by pushing them into the cloud.
“You only get out of it what you put into it” is literal here: You can get more out of the cloud by processing your data directly in the cloud.
When you “push down” your processing into a data source (like a data lake or warehouse), you’re doing your prepping and analyzing right there in the source instead of moving the data around, saving costs and getting runtimes from minutes to seconds.
Alteryx supports in-database processing across data services, including cloud-native platforms like Amazon Redshift, Azure Synapse, Databricks, and Snowflake. Using those cloud resources means more scalability and processing power for bigger projects. Chick-Fil-A, for one, leveraged in-database processing with Redshift to develop its loyalty program.
Scale your resources to handle demanding data workloads.
Not every workload is a fit for the cloud. But one workload that loves the cloud? Your highly variable, rapidly growing data workloads.
As datasets grow larger and you execute more advanced workloads like machine learning, you’ll need more storage and computing power to avoid bottlenecks. But you might not need those resources all the time. The cloud makes it possible to spin up resources only when you’re using them – if you’re a brewery gearing up for Oktoberfest, you might be dealing with a seasonal spike in sales data that you don’t need to manage year-round.
By using Alteryx with a cloud provider, you can use that cloud’s scalability for your data workloads instead of building your own infrastructure. For instance, Alteryx Server on AWS supports scaling for the large training datasets used for machine learning.
Take a best-of-breed approach when choosing solutions.
We’re in a multi-cloud, multi-deployment world. You’ve got the whole cloud ecosystem to choose from for your data solutions, from storage to analytics, to visualization. Just like you wouldn’t use the treadmill for every type of workout, you don’t need to use the same platform for every data task. But to make this work, you need ecosystem compatibility. Alteryx makes it seamless to “stack” with other platforms so you can choose the combination of solutions that make the most sense for your business.
For instance, your stack might look like this:
- AWS for your cloud infrastructure and storage
- Snowflake for your data warehouse
- Alteryx for your analytics
- Tableau for your visualizations
Alteryx is cloud provider agnostic, which means you can configure Alteryx to work easily with different cloud platforms to create the data architecture that works for you.
Upskill across departments and roles to benefit the entire business.
A common mistake in cloud adoption is not getting input from all departments. Cloud isn’t just for IT; everyone, regardless of background or technical skill, can get value from the cloud.
Using Alteryx in combination with cloud providers is an easy way to both upskill workers on data analytics while also leveraging the cloud’s power and scalability. Whether an employee is connecting to a cloud data storage service like Amazon S3 on Designer Desktop or prepping data in Snowflake using Designer Cloud powered by Trifacta, they’re utilizing the cloud for their functional area.
For the record, gym memberships are actually very cost-effective – if you use them. Just as you might aspire to be the person who reaps the benefits of the gym, aspire to be the business that reaps the benefits of cloud.
The difference is, using Alteryx with the cloud will be even easier and more fun than a workout!